Now that we've thoroughly discussed maturity levels and data models, it's time to get started actually building out the foundational elements of a rev ops strategy. Today, we're just going to be focusing on the foundations themselves, the four core elements that will really help you get started in creating and optimizing your revenue operation strategy. There's so much more that we could dive into if we started talking about expansion, recurring revenue, tracking the entire customer journey from start to finish. We could really get into the weeds.

So today, remember, this is just foundations. We'll definitely dive in and do rev ops two point o. But today, let's just focus on getting started. Now before diving into the specifics, let's quickly revisit the purpose of rev ops, our definition.

Revenue operations is the science of sustainable growth. We're focusing on building out the data models that will help us identify revenue leakage and friction so that we can then start to replicate what's working and optimize what's not. That's our goal for today, so let's dive in. Today, I'm going to give a high level overview of the four key areas that create the RevOps foundation.

We'll talk through life cycle stages, sales stages, source data, and your marketing to sales handoff. But be aware, this isn't going to be a how to guide for any of these processes. If you want to see an actual step by step guide for how to build out each of these and get them set up, I've included the HubSpot resources below. What we're going to focus on here is showing you what you should be working toward.

We're gonna be pulling back the curtain, so to speak, and showing you how to take your existing life cycle stage data, for example, and actually start identifying opportunities to improve your revenue operation strategy. So since I use that as the example, let's get started with life cycle stages. Life cycle stages are arguably one of the most important pieces of rev ops. They allow you to understand your customer journey in-depth from lead all the way through to customer.

This is the foundation of a properly set up CRM because it allows you to create a clear segmentation of your contacts and see their journey from start to finish. Now keep in mind there are a couple of important things to consider when looking at your life cycle stage data. First and foremost, manual updates. It is possible to manually update life cycle stages.

In fact, sometimes it's even necessary. But when it happens, you could see chaos in volume and conversion reporting. Look. There's always going to be those outlier scenarios in which manually updating a life cycle stage is necessary.

But just keep in mind, with great power comes great responsibility.

Manually update only when necessary.

Next, let's think about default automation. Any prebuilt automation or really any automation that you create is a great asset in helping you keep your lifecycle stages moving, but they can also cause records to skip lifecycle stages if they're not set up correctly, and that will just lead to inaccurate data. Always double and triple check to make sure any automation you have is pushing through your contacts and companies in the correct life cycle stage order. That way you avoid any conversion confusion later on.

A well organized CRM is crucial because it helps you segment your customers effectively, which in turn powers your reporting, workflows, and overall business strategy. Without clear segmentation, setting up downstream dependencies becomes difficult, if not impossible. Let's take another look at the Bowtie model. As we've talked about, our primary KPIs are those conversion metrics that lead you through the bow tie model, and life cycle stages provide key insight to a lot of those critical elements.

They really reflect the entire customer journey. It's from life cycle stages that you'll be able to see amount metrics, like the number of leads generated and the number of opportunities you had this quarter. Then you'll be able to get into the conversion metrics, like lead to MQL conversion, conversions from deals to customers, etcetera, etcetera. All of these are primary targets to be able to look and see where there's any leakage or friction, what's getting hung up, what you might need to work on.

For example, if you were to see your SQL to opportunities last quarter hit an all time low, what happened last quarter? This is where you need to dive in. Let me show you an example. Let's take a look at a data model in real time and identify friction somewhere in the process, say, in the conversion metrics between MQLs and SQLs specifically.

Here, when I'm looking at SQLs, I'm starting to see a trend emerging of decreasing sales qualified leads. This is a huge leakage point, and I'm going to want to dive in and investigate immediately. Update. Maybe my qualifying criteria isn't as accurate as I believed, or maybe it was accurate, but something has changed in my ICP, and I need to update it to keep up.

If this is the case, my sales reps are wasting time right now, time on leads that should never have made it to them, and they're draining revenue for the company. Your first step is to create reports that show each type of life cycle stage metric and then build out your quarter over quarter table to find the areas of opportunity. That's where you start noticing your trends. But wait.

What if I don't have quarter over quarter data? We all have been there. What if your instance is new or you just implemented a change that makes all previous life cycle stage data unreliable?

If that's the case, build out your reports anyway and start observing the metrics that are coming in. Start small. Review week over week data and spot check the results. Open up your lead list and look through the contacts.

Is everyone there truly a lead? Was this accurate? Spend this time focusing on refining what you've built. Optimize, reiterate, improve.

And then when you have enough data, start with a month over month table and work your way up to quarter over quarter and then year over year. It'll take you a while to get enough data to really start seeing trends, but it's never too early to start benchmarking your data and where you're coming from. This will be crucial later on when you're starting to notice differences. The next area that we wanna focus on are sales stages. Sales stages provide a repeatable road map that guides the sales process through the buyer's journey. These sales stages are a way to visually represent the customer journey from their perspective.

How did they find you? Well, they had a business issue, and that led them to evaluate options. Sales stages should always be representative of what the customer is doing. The steps taken by your sales team are the entry and exit gate criteria, but the stages themselves should be customer centric.

Here's an example sales process flow that we use here at RevPartners to create our sales stages. When we are thinking of the customer's journey, we're thinking of it like this. If we were going to summarize the business issue, we would summarize that by saying that's the discovery portion. That's the discovery stage.

They're out there. They know they have an issue, and they're trying to figure out what the best way to solve it would be. Then they move on to evaluating options, which we consider where we would provide a demo. They know that they have an issue, and they figured out a way that they want to solve it.

Now they need to know if we're the right one. Next comes the internal approval and the selecting of the vendor. In short, simple terms, we call this stage the go no go. Simple.

Is this going to happen or isn't it? Then there's the finalizing budget or negotiating price, which is why we aptly named this stage negotiate. We think of stage five as the pending signature stage. This is sort of the all encompassing title that we've given this stage to cover all the internal processes where a customer has to have legal review the contract, they need to get signatures from decision makers, etcetera, etcetera.

And then we finally move on to closed won. That's where, from a customer's perspective, they sign with us. They're starting to see value. Of course, if they didn't meet any of these stages, they would then fall into closed lost.

Self explanatory.

For us, we've tried to keep the process as uniform, comprehensive, and easily repeatable as possible. Why is this important? Well, because a structured sales process ensures consistency, which in turn leads to repeatable success. Studies show that companies with a defined sales process see significant increases in revenue and forecast accuracy.

What you wanna do is use each stage to signify that the opportunity is moving closer to closing, which can then help you forecast closing rates and identify friction points. For example, let's take a look at some of the metrics the sales stages provide and see how they fit into our strategy. We're looking at the bow tie model again, but now we're thinking about it in terms of the sales stages. How do they contribute?

The KPIs that they bring to the table are things like number of sales qualified leads generated, number of customers generated, things like the conversion metrics from SQLs to deals and the time in deal stages.

This one is a pretty big one because if you're starting to see your deal stage durations get longer and longer, could indicate that your sales team is either spread too thin and not able to work deals quickly enough or that deals are stalling out for unknown reasons. It helps you be able to dive in, and that's not all. Sales stages, like life cycle stages, feed into the overall data model. Metrics like top level KPIs, like average deal size closed by quarter compared to the amount of deals closed by quarter can really help you paint a more accurate picture of where your business stands.

How so? Well, let's take a deeper look at the average deal size by quarter example. So using the data model here, if I were to just look at deals closed won, I would see that the number is increasing, and that's good. I might even get excited.

But then when I look beside it at the average deal size by quarter, that's when I start to see what could be an alarming trend. Deals are getting smaller. This may lead me down a rabbit hole. Do I need to push harder for larger deals?

Should I implement an upgrade or an upsell add on initiative? Is my revenue actually still balanced because while the deals are smaller, there are more of them? This is what I mean by using this foundation you're building to create a comprehensive picture. You do wanna drill down and find answers and see what's happening, but always remember that each of these things work together, and you have to look at the big picture to really get an accurate view.

Okay. We've talked about how contacts and companies move through the sales process and how we are measuring deals. Now let's back up and actually look at how we got contacts in the first place. When we talk about source data, we're talking about where your contacts are actually coming from, specifically, what channels are bringing them in.

Learning this tells us which channels are the most effective. It provides the foundation for your marketing attribution and allows you to align your goals, efforts, and spending across the organization.

Here's the thing, though. Sometimes the source data coming in is broader or differently segmented than you and your unique business model actually needs. That's where taking it a step further and customizing those channels really becomes the MVP. What do I mean by that?

Well, let's take a harder look at original sources, which HubSpot automatically recognizes for your contacts and segments into nine specific categories. HubSpot's nine original source categories are organic search, paid search, email marketing, organic social, paid social, direct traffic, referrals, other campaigns, and offline sources. Seeing these sources and even more so their drill down data is extremely beneficial to your marketing efforts. It's what helps you determine whether your paid social campaign is paying off or if that email marketing campaign you're running needs a little extra help.

This is what will help you create a more effective strategy. Now when it comes to your revenue operation strategy, these sources offer an opportunity for you to dive deeper into your life cycle stage data. Remember how I said all of these would work together? Let's take a look at an example of this in this data table.

We got two thousand one hundred and seventy seven leads in quarter three, but what channels did they come from? What actually drove them to us in the first place? As we can see here, we have nine hundred and four leads coming in just in quarter three from email marketing. That's more than triple what email marketing brought in in any other quarter.

Must have been some email campaign. What that tells me is that I definitely wanna dig in. What was it about that campaign that caught attention? Was it the timing?

Was it the segmentation?

Did we get really lucky with the emails? What worked? We wanna replicate that. I can also see here that paid social did not perform well that quarter. But, of course, I am just looking at leads themselves in a silo. It could be that the paid social campaign did run well, and we had plenty of sessions and even made some prospects from it. They just didn't convert to leads.

Or, alternatively, it could be that we just didn't run any new paid social campaign that quarter because all efforts were on email marketing. If that's the case, that's something I definitely want to note and then use this as benchmarking data. Because, basically, what this is telling me is that I got fifty five leads from paid social without doing anything new on there. From now on then, fifty five leads is my goal starting point.

That's how you keep refining and improving based on everything you learn, the good and the not so good. So that's what you wanna work toward with your original source data. But as I mentioned earlier, you could also take it even further. Let's take the same data we were just looking at, but flip some of the numbers around.

Okay. With this report, I see that I have nine hundred and four leads coming from offline sources, but that's a pretty broad category. In order to learn exactly which offline source is the top performer, you'd have to really focus on the drill downs. Those would give you more information on whether those nine hundred and four leads came from list imports or if they came from an integration or if sales manually created tons of new leads in an effort to, say, focus on target accounts without having any more information.

You're just guessing at this point. That's why some companies like to take it a step further. Here at RevPartners, we use additional properties called lead acquisition channel and lead acquisition channel drill downs one and two. These properties actually segment offline sources further and even customize them to fit our business model and our demand generation efforts.

For example, here at RP, we really like to label specific conferences like inbound, or we like to have referral sites like g two listed. This helps us personalize our data to really surface the things that are most important to us, and it provides us even more detail around the where the leads are coming from. The more you know about what brings people to you, the better you can invest your time, effort, and resources. And now we've reached the final piece of the revenue operations foundation, the marketing to sales handoff.

We see now how in-depth we can get with our contacts. We see how they're moving through the sales cycle, how their deals are progressing.

But what about the crucial moment between marketing owned efforts and sales owned efforts? This is the area where leakage is most commonly found because it's so easy for leads to fall through the cracks if sales and marketing teams aren't perfectly aligned. So how do we do that? How do we reevaluate and ensure our handoff is tight and efficient?

Two words, lead statuses. Lead statuses are the cornerstone of a superior marketing to sales strategy. For example, let's go back to our data table. If I'm beginning to see a downward trend in conversion metrics like MQL to SQL or a significant drop off in MQLs and SQLs to deal creation, I'm gonna dive in and dig around. I could find that the qualification is off, like we've talked about, or I could find some friction in the sales process, such as not having enough sales team members to adequately field the deals. But I could also find that what's actually being stalled is the follow-up.

Leads either aren't being passed through or aren't being picked up. If we wanna monitor this portion of our revenue leakage, it's pivotal to have clearly defined lead statuses so that you can keep track of where each contact is in their journey. Remember, life cycle stages and deal stages should really never move backward, which means that sometimes if they stall, you could see a contact or a deal stuck in that stage for a while. If that's the case, you really need more information on exactly what's happening.

Creating detailed lead statuses and cementing the marketing to sales handoff is your answer. That's gonna be the final piece in ensuring you can always find the why behind the data you're reviewing. And there you have it. Today, we've laid out the foundational elements of RevOps data, focusing on life cycle stages, sales stages, lead sources, and marketing to sales handoffs.

These components are the building blocks that will support your entire revenue operation strategy. Now you have the tools you need to start visualizing your data, understanding the story it's telling you, and using that information to enhance your revenue operation strategy. It's time for you to get out there and start building.